CAREER: Enhancing Data Center Storage System with Persistent Memory

职业：利用持久内存增强数据中心存储系统

• 批准号: 1829524
• 负责人: Jishen Zhao
• 金额: $ 45.42万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-01-01 至 2024-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1829524&HistoricalAwards=false
• 关键词: CAREER; Enhancing; Data; Center; Storage

Persistent memory technique is envisioned to revolutionize data center storage systems. Its unpredictable performance, energy, and cost benefits can adversely affect productivity, efficiency, and profit in data centers. Though promising, this technical transition can fundamentally change the decades-long memory and storage system design assumptions and introduce critical design challenges. For example, new performance landscape can change the energy efficiency model of data centers and break the existing load balance across various system resources; traditional data reliability schemes can become suboptimal due to the discrepant failure patterns and reliability issues of new memory technologies; current applications and system software may not fully exploit the benefits offered by persistent memory. This research focuses on enhancing the performance, energy-efficiency, and reliability of data center storage system by fully exploiting the potential of persistent memory. The central approach is to rethink data center architecture design strategies and memory/storage stack management, making them persistent memory aware. The project devises fundamental techniques in efficiency modeling, load balancing of critical system resources, and low-cost reliability guarantee across single server memory/storage stack and distributed storage systems. The project also enhances a set of key data center applications by leveraging persistent memory. It is expected that research ideas developed in this project will enable significantly improved access performance, energy efficiency, reliability, and lifetime in data center memory and storage systems, taking a large step in making our daily lives more productive.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

持续的内存技术被设想为彻底改变数据中心存储系统。其不可预测的绩效，能源和成本收益可能会对数据中心的生产率，效率和利润产生不利影响。尽管很有希望，但这种技术过渡可以从根本上改变数十年的内存和存储系统设计假设，并引入关键的设计挑战。例如，新的性能格局可以改变数据中心的能源效率模型，并破坏各种系统资源的现有负载平衡；由于新记忆技术的差异失败模式和可靠性问题，传统的数据可靠性方案可能会次优。当前的应用程序和系统软件可能无法完全利用持续内存提供的好处。这项研究重点是通过充分利用持续记忆的潜力来增强数据中心存储系统的性能，能源效率和可靠性。中心方法是重新考虑数据中心体系结构设计策略和内存/存储堆栈管理，使它们保持持久的内存意识。该项目在效率建模，关键系统资源的负载平衡以及单个服务器内存/存储堆栈和分布式存储系统中的低成本可靠性保证中设计了基本技术。该项目还通过利用持久内存来增强一组关键数据中心应用程序。预计该项目中开发的研究思想将能够显着提高数据中心记忆和存储系统中的访问性能，能源效率，可靠性和寿命，从而迈出了很大一步，使我们的日常生活提高了生产力。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力和更广泛的影响来通过评估来获得的支持。

项目成果

Vorpal: Vector Clock Ordering For Large Persistent Memory Systems

Vorpal：大型持久内存系统的矢量时钟排序

• DOI: 10.1145/3293611.3331598
• 发表时间: 2019
• 期刊: ACM Symposium on Principles of Distributed Computing
• 作者: Korgaonkar, Kunal;Izraelevitz, Joseph;Zhao, Jishen;Swanson, Steven
• 通讯作者: Swanson, Steven

Processing-in-Memory for Energy-Efficient Neural Network Training: A Heterogeneous Approach

• DOI: 10.1109/micro.2018.00059
• 发表时间: 2018-10
• 期刊: 2018 51st Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)
• 作者: Jiawen Liu;Hengyu Zhao;Matheus A. Ogleari;Dong Li;Jishen Zhao

Binary Star: Coordinated Reliability in Heterogeneous Memory Systems for High Performance and Scalability

双星：异构内存系统中协调可靠性以实现高性能和可扩展性

• DOI: 10.1145/3352460.3358262
• 发表时间: 2019
• 期刊: IEEE/ACM International Symposium on Microarchitecture
• 作者: Liu, Xiao;Roberts, David;Ausavarungnirun, Rachata;Mutlu, Onur;Zhao, Jishen
• 通讯作者: Zhao, Jishen

SubZero: zero-copy IO for persistent main memory file systems

SubZero：持久主内存文件系统的零拷贝 IO

• DOI: 10.1145/3409963.3410489
• 发表时间: 2020
• 期刊: ACM SIGOPS Asia-Pacific Workshop on Systems (APSys
• 作者: Kim, Juno;Soh, Yun Joon;Izraelevitz, Joseph;Zhao, Jishen;Swanson, Steven
• 通讯作者: Swanson, Steven

Characterizing and Modeling Non-Volatile Memory Systems

• DOI: 10.1109/micro50266.2020.00049
• 发表时间: 2020-10
• 期刊: 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO)
• 作者: Zixuan Wang;Xiao Liu;Jian Yang-;Theodore Michailidis;S. Swanson;Jishen Zhao